Python for Finance with Zipline and Quantopian

Learn to build automated trading strategies and financial analysis tools using Python, Zipline, and Quantopian in this comprehensive tutorial series spanning over 4 hours. Master the fundamentals of algorithmic trading by creating, backtesting, and implementing trading strategies with real market data. Explore essential concepts including stop-loss mechanisms, target achievement strategies, and short selling techniques while working with fundamental company data. Develop advanced trading logic incorporating sentiment analysis signals and learn to use Quantopian's Fetcher for external data integration. Build machine learning frameworks for financial prediction, create classifier feature sets, and test ML-based trading strategies. Understand hedge fund objectives and financial market dynamics while gaining hands-on experience with paper trading on Quantopian. Master the Pipeline API for efficient data processing and strategy development, progressing from basic programming concepts to sophisticated automated trading systems with leverage considerations.

Syllabus

[See Description] Programming for Finance with Python and Quantopian and Zipline Part 1
[See Description] Programming for Finance Part 2 - Creating an automated trading strategy
[See Description] Programming for Finance Part 3 - Back Testing Strategy
[See Description] Accessing Fundamental company Data - Programming for Finance with Python - Part4
[See Description] Back-testing our strategy - Programming for Finance with Python - part 5
[See Description] Strategy Sell Logic with Schedule Function with Quantopian - Python for Finance 6
[See Description] Stop-Loss in strategy - Python for Finance with Quantopian and Zipline 7
[See Description] Achieving Targets and Shorting - Python for Finance with Zipline and Quantopian 8
[See Description] Quantopian Fetcher - Python for Finance with Zipline and Quantopian 9
[See Description] Trading Logic with Sentiment Analysis Signals - Python for Finance 10
[See Description] Shorting based on Sentiment Analysis signals - Python for Finance 11
[See Description] Paper Trading a Strategy on Quantopian - Python for Finance 12
[See Description] Understanding Hedgefund and other financial Objectives - Python for Finance 13
[See Description] Building Machine Learning Framework - Python for Finance 14
Creating Machine Learning Classifier Feature Sets - Python for Finance 15
[See Description] Creating our Machine Learning Classifiers - Python for Finance 16
Testing our Machine Learning Strategy - Python for Finance 17
[See Description] Leverage - Python for Finance with Quantopian and Zipline 18
[See Description] Pipeline API Intro - Python for Finance with Quantopian and Zipline 19
[See Description] Pipeline Tutorial - Python for Finance with Quantopian and Zipline 20